Control Of Synchronous Reluctance Motor Research Articles

Design of a Research Laboratory Drive System for a Synchronous Reluctance Motor for Vector Control and Performance Analysis

Motor-drive systems have the most significant share in industrial energy consumption, which requires a deep study in every aspect of the field. This paper presents a synchronous reluctance motor (SynRM) drive system based on Plecs RT box 1. The system’s design provides the opportunity for the open-loop and closed-loop control of the motor and a characteristic performance analysis of the motor. This paper focuses on the hardware implementation of a research laboratory setup and the precise vector control of the SynRM in real-time. The application of the digital controller and inverter to drive SynRM is examined. The voltage, current, and speed transducers were employed for monitoring the protective measures and to control the motor in the closed-loop. The design of the signal conditioning and the intermediary cards for isolation and data acquisition are described in detail. An algorithm is proposed to measure the whole system parameters, including motor, inverter, and cables. Thanks to the RT box 1, the principle of real-time simulation of control algorithms is investigated, and the rapid control prototyping of field-oriented control (FOC) of SynRM was implemented. The simulation of the system was carried out in the Plecs platform, and the results are presented. The experimental results of the implemented control algorithms validate the setup’s performance and the control algorithm. Finally, as a study of the motor’s performance, the efficiency map of the motor is drawn in different speed and torque ranges.

Model-Free Predictive Current Control of Synchronous Reluctance Motor Drives for Pump Applications

Climate changes and the lack of running water across vast territories require the massive use of pumping systems, often powered by solar energy sources. In this context, simple drives with high-efficiency motors can be expected to take hold. It is important to emphasise that simplicity does not necessarily lie in the control algorithm itself, but in the absence of complex manual calibration. These characteristics are met by synchronous reluctance motors provided that the calibration of the current loops is made autonomous. The goal of the present research was the development of a current control algorithm for reluctance synchronous motors that does not require an explicit model of the motor, and that self-calibrates in the first moments of operation without the supervision of a human expert. The results, both simulated and experimental, confirm this ability. The proposed algorithm adapts itself to different motor types, without the need for any initial calibration. The proposed technique is fully within the paradigm of smarter electrical drives, which, similarly to today’s smartphones, offer advanced performance by making any technological complexity transparent to the user.

Adaptive Complementary Sliding Mode Control for Synchronous Reluctance Motor With Direct-Axis Current Control

In order to design a high-performance synchronous reluctance motor (SynRM) drive system, a novel adaptive complementary sliding mode (ACSM) speed control and an effective <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current control (EDCC) are proposed in this article. First, a classical proportional-integral based field-oriented control of the SynRM drive with a constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is introduced. However, the constant <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is obtained by trial and error method or satisfying the minimum excitation current of the SynRM. More importantly, the constant value of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current command is not suitable for the highly nonlinear and time-varying SynRM drive at the varied load torque conditions. Therefore, an ACSM speed control with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current control (ACSMSC-DCC) system is designed for the speed regulation of the SynRM. The ACSM speed control is proposed to generate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis current commands, and an EDCC by using the stator flux estimator is proposed to produce the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis current commands. Finally, the proposed ACSMSC-DCC system is implemented in a 32-bit floating-point digital signal processor TMS320F28075 and its effectiveness are verified by some experimental results.

Artificial Neural Network-Based Gain-Scheduled State Feedback Speed Controller for Synchronous Reluctance Motor

Abstract This paper focuses on designing a gain-scheduled (G-S) state feedback controller (SFC) for synchronous reluctance motor (SynRM) speed control with non-linear inductance characteristics. The augmented model of the drive with additional state variables is introduced to assure precise control of selected state variables (i.e. angular speed and d-axis current). Optimal, non-constant coefficients of the controller are calculated using a linear-quadratic optimisation method. Non-constant coefficients are approximated using an artificial neural network (ANN) to assure superior accuracy and relatively low usage of resources during implementation. To the best of our knowledge, this is the first time when ANN-based gain-scheduled state feedback controller (G-S SFC) is applied for speed control of SynRM. Based on numerous simulation tests, including a comparison with a signum-based SFC, it is shown that the proposed solution assures good dynamical behaviour of SynRM drive and robustness against q-axis inductance, the moment of inertia and viscous friction fluctuations.

The Impact of the Control Strategy in Flux Observer Based Sensorless Control of Synchronous Reluctance Motors

The Impact of the Control Strategy in Flux Observer Based Sensorless Control of Synchronous Reluctance Motors

Robust Scalar Control of Synchronous Reluctance Motor With Optimal Efficiency by MTPA Control

In order to achieve improved performance and efficiency of domestic and industrial fan/pump applications using low-cost solutions, the synchronous reluctance motors (SynRMs) remains a better choice than induction motors (IMs) which are still widely used for such applications despite its low efficiency during low speed operation. However, due to the lack of self-start capability the SynRMs need external drive and speed control algorithm to properly operate, which increases the production cost. For the purpose of providing low cost solutions for the SynRMs speed control, this paper presents a stable, reliable and robust scalar control for SynRMs. This control strategy implements the maximum torque per ampere loop for high efficiency operation and online parameter estimation for robust performance. The proposed solution presented in this paper can be implemented using a low cost MCU in PWM inverter with lower carrier frequency, thereby making the low cost SynRM drive for fan/pump application feasible and practical.

Model-Free Predictive Current Control for SynRM Drives Based on Optimized Modulation of Triple-Voltage-Vector

A model-free predictive current control for synchronous reluctance motor drives based on triple-voltage-vector with optimized duty ratio modulation is presented in this paper. The proposed scheme introduces an effective and low complexity strategy of selecting candidate voltage vectors to largely reduce computational loadings. First, the basic voltage vectors are organized to apportion six regions, representing six composite switching modes. Each region comprises two active voltage vectors and a zero voltage vector modulated by distinct duty ratios. The scheme starts from the selection of an initial basic voltage vector corresponding to a predefined cost function. The second candidate voltage vector then follows, which is chosen from the region adjacent to the initial one. The third vector is a default zero voltage vector. As a result, voltage vectors outside the selected regions are excluded from the process. Moreover, the adjustable feature makes the optimization of duty ratios adaptive. Finally, the proposed method is experimentally put to tests under various operating conditions utilizing the synchronous reluctance motor drives. Experimental results are presented to demonstrate the effectiveness of the proposal.

Hermite neural network-based second-order sliding-mode control of synchronous reluctance motor drive systems

This paper proposes a novel Hermite neural network-based second-order sliding-mode (HNN-SOSM) control strategy for the synchronous reluctance motor (SynRM) drive system. The proposed HNN-SOSM control strategy is a nonlinear vector control strategy consisting of the speed control loop and the current control loop. The speed control loop adopts a composite speed controller, which is composed of three components: 1) a standard super-twisting algorithm-based SOSM (STA-SOSM) controller for achieving the rotor angular speed tracking control, 2) a HNN-based disturbance estimator (HNN-DE) for compensating the lumped disturbance, which is composed of external disturbances and parametric uncertainties, and 3) an error compensator for compensating the approximation error of the HNN-DE. The learning laws for the HNN-DE and the error compensator are derived by the Lyapunov synthesis approach. In the current control loop, considering the magnetic saturation effect, two composite current controllers, each of which comprises two standard STA-SOSM controllers, are designed to make direct and quadrature axes stator current components in the rotor reference frame track their references, respectively. Comparative hardware-in-the-loop (HIL) tests between the proposed HNN-SOSM control strategy and the conventional STA-SOSM control strategy for the SynRM drive system are performed. The results of the HIL tests validate the feasibility and the superiority of the proposed HNN-SOSM control strategy.

Robust Control of Synchronous Reluctance Motors by Means of Linear Matrix Inequalities

This article proposes an alternative for robust control of synchronous reluctance motors using linear matrix inequalities to obtain fixed gains that ensure current and speed regulation, under parameter uncertainties and variations. The proposed design procedure is based on a polytopic model, which takes into account: i) uncertainties and variations of the mechanical and electrical parameters of the motor, ii) one step delay from digital implementation of the control law, and iii) internal model based controllers to guarantee reference tracking. Less conservative linear matrix inequalities, relying on slack variables, ensure robust pole location and certify the closed-loop stability for the entire domain of uncertain and time-varying motor parameters, based on parameter-dependent Lyapunov functions. The linear matrix inequalities ensure a fast and systematic computation of the control gains, that are also easy to be implemented, not adding computational complexity when compared, for instance, to usual strategies based on PI controllers. Experimental results for a 2.2 kW commercial motor are provided, validating the proposed procedure, and illustrating good tracking of currents and speed references, with suitable dynamic responses and reduced cross-coupling effects, when compared to sliding mode and PI controllers.

Torque-Sensorless Ripple-Reduction Torque Control of Synchronous Reluctance Motors

Torque-Sensorless Ripple-Reduction Torque Control of Synchronous Reluctance Motors

Pole Reduction Concept for Control of Synchronous Reluctance Motor-Based Solar Photovoltaic Water Pumping System for Improved Performance

This article deals with an improved control for synchronous reluctance motor (SyRM)-based photovoltaic (PV) water pumping system, eliminating the speed controller of position sensorless field-oriented control (FOC) of SyRM. The solar water pump drive involves two stages of power conversion. The reference quadrature axis current of FOC is estimated from available PV array power that is being continuously tracked for maximum power point. This eliminates the requirement of an additional speed controller. This improves the transient behavior of overall control under dynamic conditions such as varying solar radiation. A pole is eliminated from overall characteristic equation of open-loop dc link voltage control transfer function. As a result, a single proportional integrator controller satisfactorily controls the whole pumping system. The system is much easier to tune, and by default, immune to aging and variation in pump's constant. This improves fidelity and reduces the overall cost of the system. Performance of this system is validated through a developed laboratory prototype of solar PV array-fed SyRM drive for water pumping. The overall system performance is examined under different environmental conditions.

Design and Speed Control of SynRM using Cascade PID Controller with PSO Algorithm

In recent years, the variable speed motor drive is supported over a fixed speed motor drive as per essentialness safeguarding, speed or position control and improvement of transient response characteristics. The aim of any speed controller is to take main signal that represent the reference speed and to drive the framework at that reference speed. This paper exhibits the design, simulation and control of synchronous reluctance motor (SynRM). In addition, the motor speed is controlled by utilizing a conventional PID controller that has been used from the cascaded structure. The Particle Swarm Optimization (PSO) was used to find the best parameters of the PID controller. Lead-Lag controller presents from the cascaded controller as the following period of control. The Space vector pulse width modulation (SVPWM) plot has been proposed to control the motor and make the motor work with no rotor confine contingent upon the info parameters that utilization in the simulation. An examination between both of PID tuned and PSO tuned controller affirms that the PSO gives dazzling control highlights to the motor speed and have an edge over the physically changing controller. Thus, this paper present investigation and simulation for the most precise procedures to control the speed reaction and torque reaction of synchronous reluctance motor (SynRM).©2020. CBIORE-IJRED. All rights reserved

Design and Experimental Evaluation of a 12 kW Large Synchronous Reluctance Motor and Control System for Elevator Traction

Recently, a new type of motor, synchronous reluctance motor (SRM), has attracted wide attention from academia and industry because of its potential applications in fans, pumps, and elevator traction systems. Compared with traditional motors, these motors have lower eddy-current loss, less torque ripple, reduced noise, smaller moment of inertia, and faster dynamic response, and they provide a greater operating efficiency and safety and are simpler and easier to maintain. However, the ontology design and operation control of SRMs continue to be significant hurdles that must be overcome prior to practical implementation. In order to facilitate the practical application of SRMs in industry, at the invitation of an elevator company, we designed a large SRM for elevator traction. Herein, we describe the design of the proposed system and present a theoretical analysis of the system. Furthermore, we fabricate a real prototype and the corresponding control system and perform an experimental test under the rated operating conditions and $1.5\times $ overload conditions in order to verify the SRM’s performance. The results of the experimental testing were satisfactory and consistent with the theoretical calculations. At present, we have entered the stage of small-batch trial production and we expect to ultimately implement this novel design. Further, the approach to ontology design and operation control in this study can be used to inform the future development of novel SRMs.

Adaptive Backstepping Control for Synchronous Reluctance Motor Based on Intelligent Current Angle Control

The design and analysis of a novel current angle-based adaptive backstepping (ABS) speed control system for a synchronous reluctance motor (SynRM) drive system is presented in this article. First, a proportional-integral control system with field-oriented control is described. Owing to the unmodeled dynamics and magnetic saturation effects of the SynRM, currently, there is no predominant way to design the command of the d-axis current for the SynRM. Therefore, an ABS based on the current angle control (ABS-CAC) system is designed for the speed tracking of SynRM. The ABS speed tracking control is proposed to generate the stator current command, and a lookup table of the results of maximum torque per ampere (MTPA) analysis by using the finite element analysis method is proposed to provide the current angle commands. Moreover, to improve the transient dynamic response of SynRM under MTPA operating conditions, an intelligent speed transient control system using a recurrent Hermite fuzzy neural network is developed to generate the compensated current angle command. The proposed intelligent ABS-CAC is implemented in a 32-bit floating-point digital signal processor TMS320F28075. Finally, some experimental results are provided to demonstrate the robustness and effectiveness of the proposed control system.

Adaptive Maximum Torque per Ampere Control of Synchronous Reluctance Motors by Radial Basis Function Networks

As neodymium and other rare earth materials become a critical commodity, the exploitation of reluctance torque in synchronous motors is certainly an interesting option. Alternative motor topologies span from internal permanent magnet motors to pure reluctance machines. Anyway, any anisotropic structure suffers from some magnetic nonlinearities that call for more sophisticated models to get an efficient torque control. Neural network-based algorithms are good candidates for modeling the current-to-flux linkages curves of synchronous reluctance (SynR) motors, but so far their use was limited by the inherent complexity and the computational burden. This paper proposes the use of a special kind of neural networks, namely, the radial basis function networks, to get the magnetic model of any synchronous motor, including saturation and cross-coupling effects. Through experimental evidence, it will be shown that the structure is light enough to be implemented, trained, and self-updated online on standard high-end ac drives. The model is used to track online the maximum torque-per-ampere working point of a SynR motor drive.

Управление реактивной электрической машиной с анизотропной магнитной проводимостью ротора

Управление реактивной электрической машиной с анизотропной магнитной проводимостью ротора

Deviation Model-Based Control of Synchronous Reluctance Motor Drives With Reduced Parameter Dependency

Control issue in electrical drives mainly deals with the dynamic behavior, which is based on the deviation of variables. The deviations play a straightforward role in presenting the various capabilities and merits of the electric drive systems. This paper describes, for the first time, a deviation-based torque control of synchronous reluctance motor (SynRM) drives with no need to know the motor parameters. The proposed control system is designed by using a normalized deviation model to derive linear and simple relationships amongst different machine signals. Therefore, the commonly used proportional–integral current regulators are replaced by novel deviation equations. As a result, the proposed approach provides facilities to electric drives, including control system simplicity, parameter independency, and no need for controller tuning. The theoretical findings are verified by those experiments. The obtained results are reported for a typical SynRM drive. In addition, performance comparison of the control system with a general PI controller-based field-oriented control scheme is carried out. It is expected that the proposed approach contributes to other electrical drives to simplify the machine equations, reduce control complexities, such as the number of conventional controllers, and overcome the problem of machine parameter dependency.

An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

The performances of a model predictive control algorithm largely depend on the knowledge of the system model. A model-free predictive control approach skips all the effects of parameters variations or mismatches, as well as of model nonlinearity and uncertainties. A finite-set model-free current predictive control is proposed in this paper. The current variations predictions induced by the eight base inverter voltage vectors are estimated by means of the previous measurements stored into lookup tables. To keep the current variations information up to date, the three current measurements due to the three most recent feeding voltages are combined together to reconstruct all the others. The reconstruction is performed by taking advantage of the relationships between the three different base voltage vectors involved in the process. In particular, 210 possible combinations of three-state voltage vectors can be found, but they can be gathered together in six different groups. A light and computationally fast algorithm for the group identification is proposed in this paper. Finally, the current reconstruction for the prediction of future steps is thoroughly analyzed. A compensation of the motor rotation effect on the input voltages is proposed, too. The control scheme is evaluated by means of both simulation and experimental evidences on two different synchronous reluctance motors.

An Accurate Self-Commissioning Technique for Matrix Converters Applied to Sensorless Control of Synchronous Reluctance Motor Drives

The compensation of converters’ nonlinear voltage error is crucial in the encoder-less control of ac motor drives. In this paper, a new self-commissioning and compensation method is proposed for matrix converters (MCs). Similar to what done in the past for voltage source inverters, the MC voltage error is identified before the drive start and stored in a lookup table, later used for error compensation and accurate voltage estimate. Different from what observed in the past, the effect of parasitic capacitors on nonlinear voltage error of MCs in four-step current-based commutation is observed and studied. Eventually, this method is applied to the sensorless control of a synchronous reluctance motor drive, using the direct flux vector control concept. Experimental results are presented to validate the effectiveness of the proposed self-commissioning in improving the performance of sensorless control at standstill and low speed.

Enhanced Emotional and Speed Deviation Control of Synchronous Reluctance Motor Drives

This paper proposes an enhanced brain emotional learning-based intelligent controller for synchronous reluctance motor (SynRM) drives. The controller is based on an emotional learning and decision making mechanism in the brain via emotional cues and sensory inputs. Furthermore, the enhanced controller improves learning process in the amygdala to avoid internal instability. In spite of the development for interior-stability, the proposed controller could keep its ability to deal with challenges related to SynRM drives. The proposed controller is also contributed with a speed deviation control. The new deviation controller is based on model but parameter-free. The updated system is implemented in real-time by a PC-based three-phase 370 W laboratory SynRM. The proportional-integral (PI) controllers used in a standard rotor field-oriented control structure are replaced with those of the proposed method. The speed and d -axis stator current references are accurately tracked. The achieved performances by the proposed controllers are compared with those of optimized conventional PI controller in different situations. Considering the results, the enhanced system shows superiority over the traditional system in terms of fast dynamics, easy tuning, and robustness against disturbances and parameter variations.